Zobrazeno 1 - 10 of 32 pro vyhledávání: '"Diane Gan"'
1
Akademický článek
An Investigation to Detect Banking Malware Network Communication Traffic Using Machine Learning Techniques
Autor: Mohamed Ali Kazi, Steve Woodhead, Diane Gan
Publikováno v: Journal of Cybersecurity and Privacy, Vol 3, Iss 1, Pp 1-23 (2022)
Banking malware are malicious programs that attempt to steal confidential information, such as banking authentication credentials, from users. Zeus is one of the most widespread banking malware variants ever discovered. Since the Zeus source code was
Externí odkaz: https://doaj.org/article/2c4d79c1d78747af984fd543f4e87d79
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2
Akademický článek
Cloud-Based Cyber-Physical Intrusion Detection for Vehicles Using Deep Learning
Autor: George Loukas, Tuan Vuong, Ryan Heartfield, Georgia Sakellari, Yongpil Yoon, Diane Gan
Publikováno v: IEEE Access, Vol 6, Pp 3491-3508 (2018)
Detection of cyber attacks against vehicles is of growing interest. As vehicles typically afford limited processing resources, proposed solutions are rule-based or lightweight machine learning techniques. We argue that this limitation can be lifted w
Externí odkaz: https://doaj.org/article/1089faa40e054bbc863de673054b2d94
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3
Akademický článek
You Are Probably Not the Weakest Link: Towards Practical Prediction of Susceptibility to Semantic Social Engineering Attacks
Autor: Ryan Heartfield, George Loukas, Diane Gan
Publikováno v: IEEE Access, Vol 4, Pp 6910-6928 (2016)
Semantic social engineering attacks are a pervasive threat to computer and communication systems. By employing deception rather than by exploiting technical vulnerabilities, spear-phishing, obfuscated URLs, drive-by downloads, spoofed websites, scare
Externí odkaz: https://doaj.org/article/053bd208536544268def780a210f20dc
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4
Akademický článek
Social Networking Privacy—Who’s Stalking You?
Autor: Diane Gan, Lily R. Jenkins
Publikováno v: Future Internet, Vol 7, Iss 1, Pp 67-93 (2015)
This research investigates the privacy issues that exist on social networking sites. It is reasonable to assume that many Twitter users are unaware of the dangers of uploading a tweet to their timeline which can be seen by anyone. Enabling geo-locati
Externí odkaz: https://doaj.org/article/fbaae715800f47d1a672f370d5ebf3d5
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5
Akademický článek
A Review of Cyber Threats and Defence Approaches in Emergency Management
Autor: Tuan Vuong, Diane Gan, George Loukas
Publikováno v: Future Internet, Vol 5, Iss 2, Pp 205-236 (2013)
Emergency planners, first responders and relief workers increasingly rely on computational and communication systems that support all aspects of emergency management, from mitigation and preparedness to response and recovery. Failure of these systems
Externí odkaz: https://doaj.org/article/6ac59dbed7f54bdf93ccbe3cad79a847
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7
Detecting the Zeus Banking Malware Using the Random Forest Binary Classification Algorithm and a Manual Feature Selection Process
Autor: Mohamed Ali Kazi, Diane Gan, Steve Woodhead
Publikováno v: Communications in Computer and Information Science ISBN: 9789811548246
SSCC
The Zeus malware is one of the most prolific banking malware variants ever to be discovered and this paper examines how the Zeus malware network traffic can be detected using the Random Forest machine learning algorithm. The key to this paper is that
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b5a5dc57f597007518478831346db9db
https://doi.org/10.1007/978-981-15-4825-3_23
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9
Facilitating forensic examinations of multi-user computer environments through session-to-session analysis of Internet history
Autor: C. S. Ierotheou, Diane Gan, David Gresty, George Loukas
Publikováno v: Digital Investigation. 16:S124-S133
This paper proposes a new approach to the forensic investigation of Internet history artefacts by aggregating the history from a recovered device into sessions and comparing those sessions to other sessions to determine whether they are one-time even
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0fe4954604e0c400bab83995b4bb3ea1
https://doi.org/10.1016/j.diin.2016.01.015
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10
Cloud-based cyber-physical intrusion detection for vehicles using Deep Learning
Autor: Ryan Heartfield, Georgia Sakellari, George Loukas, Yongpil Yoon, Diane Gan, Tuan Vuong
Publikováno v: IEEE Access
IEEE Access, Vol 6, Pp 3491-3508 (2018)
Detection of cyber attacks against vehicles is of growing interest. As vehicles typically afford limited processing resources, proposed solutions are rule-based or lightweight machine learning techniques. We argue that this limitation can be lifted w
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f66fa42a753a4039cf526d9457d8c980
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